Proteomics and genomics projects have yielded a detailed inventory of proteins in a cell. However, little is known about how these proteins are spatially and temporally arranged within the cell. Such knowledge is essential to understanding how proteins contribute to the structure and function of a living cell. Just as words must be assembled into sentences, paragraphs, and chapters to make sense, vital cellular functions are performed by structured assemblies (or complexes) of proteins rather than individual molecules. Often, these complexes comprise tens or hundreds of proteins. This proposal describes a set of computational methods that will exploit and integrate several kinds of emerging experimental data to uncover the structure and dynamics of protein complexes, toward the ultimate goal of achieving a mechanistic understanding of the cell. In particular, we will characterize proteome organization on three levels through the following projects. (1) We will develop an efficient computational method to determine the structure of individual protein complexes by simultaneously fitting multiple components to cryo-electron microscopy maps. (2) We will develop advanced pattern mining methods to discover and localize unknown protein complexes in whole-cell cryoelectron tomograms - a prerequisite towards comprehensive visual proteomics. (3) We will develop simulation methods to study the systems dynamics of protein interaction networks on biologically relevant time scales and within realistic cellular environments. With these tools, we are poised to model the spatial and temporal organizations of proteome. We will freely provide software packages and source code for all methods to the scientific community.